Become Better With Biostatistics for the Non-Statistician In 10 Minutes

That statistics can be a vital decision-making tool for clinical research is well-established. It is helpful for the clinician in situations where a p-value can help determine the next steps in the development of a drug or procedure. It is thus vital for decision makers to comprehend the theory and application of statistics.

We have many statistical software applications that help in arriving at crucial decisions. However, almost all these software applications were developed for statisticians. These software applications could confound the non-statisticians. Their confusion could start with something as basic as even knowing which key to press.

In this scenario, learning how to use biostatistics and derive its benefits is important. A marathon, six-hour webinar being organized by GlobalCompliancePanel, a leading provider of professional trainings for all the areas of regulatory compliance, on October 25, will explain biostatistics for the non-statistician.

Elaine Eisenbeisz, a private practice statistician and owner of Omega Statistics, a statistical consulting firm based in Southern California, will be the expert at this webinar. Please visit https://www.globalcompliancepanel.com/virtual-seminar/6-hour-virtual-seminar-on-biostatistics-for-the-non-statistician-10307LIVE to register for this webinar.

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This webinar, designed for non-statisticians, provides a non-mathematical introduction to biostatistics. Elaine will arm the participants with all the information and skills necessary for understanding statistical concepts and findings as they apply to clinical research, and to confidently convey this knowledge to people with whom they work.

This webinar will emphasize statistical concepts, application, and interpretation, and not on mathematical formulas or actual data analysis. Participants are expected to have an elementary understanding of statistics, but this is not mandatory.

It is aimed at professionals who must understand and work with study design and interpretation of findings in a clinical or biotechnology setting.

This will be the agenda that will be covered at this webinar:

Why Statistics?

• Do we really need statistical tests?
• Sample vs. Population
• I’m a statistician not a magician! What statistics can and can’t do
• Descriptive statistics and measures of variability

The many ways of interpretation

• Confidence intervals
• p-values
• effect sizes
• Clinical vs. meaningful significance

Common Statistical Tests

• Comparative tests
• Regression analysis
• Non-parametric techniques

Bayesian Logic

• A different way of thinking
• Bayesian methods and statistical significance
• Bayesian applications to diagnostics testing
• Bayesian applications to genetics

Interpreting Statistics – Team Exercise

• Team Exercise: Review a scientific paper and learn how to
  • Interpret statistical jargon
  • Look for reproducibility, transparency, bias, and limitations
  • Convey information coherently to non-statisticians

Study power and sample size

• Review of p-value, significance level, effect size
• Formulas, software, and other resources for computing a sample size

Developing a Statistical Analysis Plan

• Using FDA guidance as a foundation, learn the steps and criteria needed to develop a statistical analysis plan (SAP).
• An SAP template will be given to all attendees.

Specialized topics/Closing Comments/Q&A

• Comparing Survival Curves
• Pharmacokinetics/Pharmacodynamics (PK/PD)
• Taking a holistic view to study design and interpretation
• Question and Answer session.

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About the Director:

Elaine brings over 30 years of experience in creating data and information solutions for industries ranging from governmental agencies and corporations to start-up companies and individual researchers. She has designed the methodology for numerous studies in the clinical, biotech, and health care fields.

She currently is an investigator on approximately 10 proton therapy clinical trials for Proton Collaborative Group, based in Illinois. She also designs and analyzes studies as a contract statistician for nutraceutical and fitness studies with QPS, a CRO based in Delaware.

How to interpret and use more than just a standard tool-box

How to apply statistics to manage risks and verify/validate processes in R&D, QA/QC, and Manufacturing, with examples derived mainly from the medical device design/manufacturing industry. The flow of topics over the 2 days is as follows:

• ISO standards and FDA/MDD regulations regarding the use of statistics.
• Basic vocabulary and concepts, including distributions such as binomial, hypergeometric, and Normal, and transformations into Normality.
• Statistical Process Control
• Statistical methods for Design Verification
• Statistical methods for Product/Process Qualification
• Metrology: QC Sampling Plans the statistical analysis of measurement uncertainty, and how it is used to establish QC specifications
• How to craft “statistically valid conclusion statements” (e.g., for reports)
• Summary recommendations

The various statistical methods used to support such activities can be intimidating. If used incorrectly or inappropriately, statistical methods can result in new products being launched that should have been kept in R&D; or, conversely, new products not being launched that, if analyzed correctly, would have met all requirements. In QC, mistakenly chosen sample sizes and inappropriate statistical methods may result in purchased product being rejected that should have passed, and vice-versa.

This provides a practical approach to understanding how to interpret and use more than just a standard tool-box of statistical methods; topics include: Confidence intervals, t-tests, Normal K-tables, Normality tests, Confidence/reliability calculations, Reliability plotting (for extremely non-normal data), AQL sampling plans, Metrology (i.e., statistical analysis of measurement uncertainty ), and Statistical Process Control. Without a clear understanding and correct implementation of such methods, a company risks not only significantly increasing its complaint rates, scrap rates, and time-to-market, but also risks significantly reducing its product and service quality, its customer satisfaction levels, and its profit margins.

• FDA, ISO 9001/13485, and MDD requirements related to statistical methods
• How to apply statistical methods to manage product-related risks to patient, doctor, and the designing/manufacturing company
• Design Control processes (verification, validation, risk management, design input)
• QA/QC processes (sampling plans, monitoring of validated processes, setting of QC specifications, evaluation of measurement equipment)
• Manufacturing processes (process validation, equipment qualification)

• QA/QC Supervisor
• Process Engineer
• Manufacturing Engineer
• QC/QC Technician
• Manufacturing Technician
• R&D Engineer

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It is important for non-statisticians to become familiar with biostatistics

Statistics is extremely useful as a decision-making tool in the clinical research arena. In areas such as working in a field where a p-value can determine the next steps on development of a drug or procedure, it is very handy, because of which it is imperative for decision makers to understand the theory and application of statistics.

Many statistical software applications have now been developed and made available to professionals. It needs to be borne in mind that these software applications were developed for statisticians, because of which its use can baffle non-statisticians. Their confusions could be as basic as pressing the right key, let alone performing the best test.

A full learning session on biostatistics for the non-statistician

A seminar from GlobalCompliancePanel, a leading provider of professional trainings for all the areas of regulatory compliance, will throw light on the importance of biostatistics for the non-statistician.

Elaine Eisenbeisz, a private practice statistician and owner of Omega Statistics, a statistical consulting firm based in Southern California, who has over 30 years of experience in creating data and information solutions for industries ranging from governmental agencies and corporations to start-up companies and individual researchers; will be the Director of this seminar.

Want to understand the importance of biostatistics for the non-statistician? Then, please enrol for this seminar by visiting It is important for non-statisticians to become familiar with biostatistics. This seminar has been pre-approved by RAPS as eligible for up to 12 credits towards a participant’s RAC recertification upon full completion.

Statistical concepts in clinical research

Designed essentially for non-statisticians; this seminar provides a non-mathematical introduction to biostatistics. It will be of high value to professionals who must understand and work with study design and interpretation of findings in a clinical or biotechnology setting.

Elaine will equip participants of this seminar with the information and skills necessary to understand statistical concepts and findings as they relate to clinical research. With this information, they will be able to confidently communicate with people with whom they need to.

Elaine will place emphasis on the actual statistical concepts, application, and interpretation. She will not go into the areas of mathematical formulas or actual data analysis. A basic understanding of statistics is desired from the participants, but is not necessary.

This course on biostatistics for the non-statistician will help professionals involved in this area, such as Physicians, Clinical Research Associates, and Clinical Project Managers/Leaders, Sponsors, Regulatory Professionals who use statistical concepts/terminology in reporting, and Medical Writers who need to interpret statistical reports.

Elaine’s agenda for this two-day seminar will consist of the following:

Why Statistics?

• Do we really need statistical tests?
• Sample vs. Population
• I’m a statistician not a magician! What statistics can and can’t do
• Descriptive statistics and measures of variability

The many ways of interpretation

• Confidence intervals
• p-values
• effect sizes
• Clinical vs. meaningful significance

Common Statistical Tests

• Comparative tests
• Regression analysis
• Non-parametric techniques

Bayesian Logic

• A different way of thinking
• Bayesian methods and statistical significance
• Bayesian applications to diagnostics testing
• Bayesian applications to genetics

Interpreting Statistics – Team Exercise

• Team Exercise: Review a scientific paper and learn how to
  • Interpret statistical jargon
  • Look for reproducibility, transparency, bias, and limitations
  • Convey information coherently to non-statisticians

Study power and sample size

• Review of p-value, significance level, effect size
• Formulas, software, and other resources for computing a sample size

Developing a Statistical Analysis Plan

• Using FDA guidance as a foundation, learn the steps and criteria needed to develop a statistical analysis plan (SAP).
• An SAP template will be given to all attendees.

Specialized topics/Closing Comments/Q&A

• Comparing Survival Curves
• Pharmacokinetics/Pharmacodynamics (PK/PD)
• Taking a holistic view to study design and interpretation
• Question and Answer session.

 

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The use of Applied Statistics for FDA Process Validation

The use of Applied Statistics for FDA Process Validation is considered a matter of very high importance in the pharmaceutical industry. The FDA’s guidance for the industry, which it called “Process Validation: General Principles and Practices”, was set up in 2011. This guideline sets the framework for Process Validation in the pharmaceutical industry. The FDA prescribes a three-stage process that any organization in the pharmaceutical industry has to set up:

1. Process Design
2. Process Qualification

• Continued Process Verification.

The Process Design stage, which is called Stage 1, is when the organization defines the commercial manufacturing process. The knowledge that the organization has gained through development and scale-up activities serves as the basis for the development of this definition.

The Process Qualification, or Stage 2, involves evaluating the process design for the purpose of determining if the process defined in Stage I has the capability for reproducible commercial manufacturing.

The next stage of the FDA process validation stage is to determine if the Process Design stage and the Process Qualification stage give the ongoing assurance that the process remains in a state of control during routine production. This is what Stage 3, the Continued Process Verification, does.

Thorough understanding of how to implement Applied Statistics for FDA Process Validation

The ways of using Applied Statistics for FDA Process Validation will be the topic of a two-day seminar that GlobalCompliancePanel, a leading provider of professional trainings for the regulatory compliance areas, will be organizing. At this seminar, Richard Burdick, Emeritus Professor of Statistics, Arizona State University (ASU) and former Quality Engineering Director for Amgen, Inc., will be the Director.

Please visit http://www.globalcompliancepanel.com/control/globalseminars/~product_id=901132SEMINAR?wordpress-SEO to register for this meaningful and highly valuable seminar on applied statistics for process validation. This course has been pre-approved by RAPS as eligible for up to 12 credits towards a participant’s RAC recertification upon full completion.

A methodical approach to implementing statistical methodologies

The focus of this two-day course on Applied Statistics for FDA Process Validation is the various ways by which a systematic approach to implementing statistical methodologies into a process validation program consistent with the FDA guidance can be established.

Dr. Burdick will begin with a primer on statistics, where he will explain how the methods of Applied Statistics for FDA Process Validation seminar can be applied in each remaining chapter.

The two fundamental requirements for Process Validation, namely the application of statistics for setting specifications and assessing measurement systems (assays), will be taken up next.

The next aspect of applied statistics Dr. Burdick will move on to is how to apply statistics through the three stages of process validation as defined by requirements in the process validation regulatory guidance documents.

Since the methods taught through all these three stages are recommended by regulatory guidance documents; this seminar on Applied Statistics for FDA Process Validation will provide references to the specific citations in the guidance documents.

The aim of this learning on Applied Statistics for FDA Process Validation is to lead participants into ways of establishing a systematic approach to implementing statistical methodologies into a process development and validation program that is consistent with the FDA guidance.

Complete learning on Applied Statistics for FDA Process Validation

Over the two days of this seminar, the participants will learn how to:

• Apply statistics for setting specifications
• Assess measurement systems (assays)
• Use Design of Experiments (DOE)
• Develop a control plan as part of a risk management strategy, and
• Ensure process control/capability.

All concepts at this Applied Statistics for FDA Process Validation seminar are taught within the three-stage product cycle framework defined by requirements in the process validation regulatory guidance documents.

Although aimed at the pharmaceutical industry, this seminar on Applied Statistics for FDA Process Validation provides a useful framework for other related industries, as well.

In this important learning on Applied Statistics for FDA Process Validation; Dr. Burdick will cover the following areas:

• Apply statistics to set specifications and validate measurement systems (assays)
• Develop appropriate sample plans based on confidence and power
• Implement suitable statistical methods into a process validation program for each of the three stages
• Stage 1, Process Design: utilize risk management tools to identify and prioritize potential critical process parameters; and define critical process parameters and operating spaces for the commercial manufacturing process using design of experiments (DOE)
• Stage 2, Process Qualification: assess scale effects while incorporating large (pilot and/or commercial) scale data; develop process performance qualification (PPQ) acceptance criteria by characterizing intra and inter-batch variability using process design data and batch homogeneity studies; and develop an appropriate sampling plan for PPQ
• Stage 3, Continued Process Verification: develop a control plan as part of a risk management strategy; collect and analyze product and process data; and ensure your process is in (statistical) control and capable.

keep enhancing FDA Process Validation

Data visualization can have a great effect on statistical presentations

It is said that a picture is worth a thousand words. This adage may appear figurative and allegorical when applied to the realm of statistics, but there is no denying the fact that a visual approach to statistics enlivens the subject like no other. A dash of pictorial work and some coloring at the right places enhance the presentation of otherwise drab statistical figures and slides dramatically.

Graphic displays illustrate the facts and truths behind statistics very artistically. They augment the appeal of what is conveyed by the statistical figures without altering or diluting the effect or the content. This is why presenting data visually is a great enhancer. It is very useful in any compliance analytics workflow.

Graphic enhancements can be used to uplift and raise the presentational aspects of statistics, but it requires skill and specific tools, because the pictorial aspect has to fit rightly into the statistical presentations. Any mismatch or mix-ups can have the opposite effect, making the statistical pictures gaudy, out of place and jarring.

Get to the ways of doing it

A two-day seminar from GlobalCompliancePanel, a highly respected provider of professional trainings for the regulatory areas, will offer thorough and complete learning on the proper ways of beautifying statistical presentations with the right mix of graphics, so that the intended purpose of embellishing is met.

James Wisnowski, who is the cofounder of Adsurgo LLC and co-author of the book, Design and Analysis of Experiments by Douglas Montgomery: A Supplement for using JMP and currently provides training and consulting services to industry and government in Design of Experiments (DOE), Reliability Engineering, Data Visualization, Predictive Analytics, and Text Mining; will be the Director at this two-day seminar.

Please visit Data visualization can have a great effect on statistical presentations  to enroll for this highly interesting seminar, which has been pre-approved by RAPS as eligible for up to 12 credits towards a participant’s RAC recertification upon full completion.

All about graphics in statistics

This seminar on data visualization will present methods using which participants can interactively discover relationships graphically. James will offer participants the foundations that will help them create better graphical information with which to accelerate the insight discovery process and improve the comprehension of reported results.

He will lead participants to an exploration of the first principles and the “human as part of the system” aspects of information visualization from multiple leading sources such as Harvard Business Review, Edward Tufte, and Stephen Few. All this will be done using representative example data sets. Best practices for graphical excellence to most effectively, clearly, and efficiently communicate a thought will be explained. He will show how to construct visualizations for univariate, multivariate, time-dependent, and geographical data. Participants are encouraged to bring laptops to follow along demonstrations in JMP (free trial download at www.jmp.com), and open source solutions such as R (https://www.r-project.org) and Tableau Public (https://public.tableau.com/s/).

Meeting the requirements of analytic solutions

As all regulated industries have now come to expect data-driven decisions; compliance regulations require analytic solutions. The starting point of these solutions is the development of data visualization for discovering relationships and finish with crisp graphs communicating results. To take the example of 21 CFR and guidance documents for the pharmaceutical, biopharmaceutical, and medical device industries; these documents specify the application of statistical methods for the following:

• Setting validation criteria and specifications
• Performing measurement systems analysis (MSA)
• Conducting stability analysis
• Using design of experiment (DOE) for process development and validation
• Developing process control charts
• Determining process capability indices.

For each of these areas, data visualization serves as the foundation. Data visualization plays a major role in varying degrees in varied areas such as:

• meeting FDA analytical requirements for third-tier critical to quality attributes for analytical bio similarity evaluations where graphical plots and tables alone may sufficiently address compliance criteria

 

• HIPAA compliance, risk management and analysis, and many others of the quality functions.

James will show how to use data visualization and optimize the effect of these areas. The following agendas will be part of the two-day presentation:

• Introduction and definitions
• Examples of data visualizations for compliance and regulated industries
• Historical context
• Characteristics of data
• Interactive data visualization exploration with Excel and websites
• Human side of data visualization
• Principles of good graphic design
• Data visualization methodology
• Best practices
• Software introduction: JMP
• Univariate plots
• Distributions and histograms
• Pie graphs, violin plots, pareto plots, box plots
• Conditional formatting
• Mulitvariate plots and heatmaps
• Correlation
• Multivariate scatterplots and density graphs
• Contour plots
• Categorical data plots: treemaps, mosaic plots
• Software introduction: R
• Software introduction: Tableau Public
• Univariate plots with R and Tableau
• Multivariate plots with R and Tableau
• Dynamic and interactive graphs
• Brushing, dynamic linking, and filtering
• Profilers on response variables and optimization
• Time series plots
• Waterfall plots
• Sparklines and trend lines
• Statistical Process Control charts
• Maps
• Text data visualization
• Dashboards
• Course summary.

 

Seminar Calendar of Upcoming Courses – June to July – 2017

GlobalCompliancePanel’s seminars are a wonderful opportunity for professionals in the regulatory compliance areas to understand the latest happenings and updates in the regulatory compliance areas and to implement them, something they need to climb in their professions. GlobalCompliancePanel brings together a few of the best recognized names in the field of regulatory compliance on its panel of experts. The result: Learning that is effective, valuable and helpful.

GlobalCompliancePanel’s experts help you unravel all the knowledge you need in all the areas of regulatory compliance. At these seminars which are held all over the globe, you get to interact with them in person, so that any doubt or clarification you have is sorted out by none other than the honcho. They help professionals like you implement the regulations and stay updated, so that regulatory compliance causes no stress for you.

GlobalCompliancePanel’s experts offer their insightful analysis into the issues that are of consequence to regulatory professionals in their daily work. Their thoughts help you implement the best practices of the industry into your work. They also offer updates on the latest regulatory requirements arising out of a host of the laws and issues related to regulatory compliance, including, but not limited to medical devices, food and beverages, pharmaceuticals, life sciences, biotechnology and pharmaceutical water systems.

Take a look at our upcoming webinars from GlobalCompliancePanel, which will put you on the road to learning about any area that is of importance to your profession. You can plan your learning from GlobalCompliancePanel by looking at our seminars in the next few weeks at locations of convenience to you. You can choose from a whole range of topics. See which among these trainings suit you: Design of Experiments (DOE) for Process Development and Validation, Writing and implementing effective SOP’s, new FSMA rules, risk management and device regulations, data integrity, combination products, and what have you!

Contact us today!
NetZealous LLC DBA GlobalCompliancePanel
john.robinson@globalcompliancepanel.com
Toll free: +1-800-447-9407
FAX : 302 288 6884
Website: http://bit.ly/Courses-June-to-July-2017

Understanding the practical application of statistics?

The application of statistical methods is specified all through 21 CFR and guidance documents for the pharmaceutical, biopharmaceutical, and medical device industries for these activities:

o  Setting validation criteria and specifications

o  Performing Measurement Systems Analysis (MSA)

o  Conducting stability analysis

o  Using Design of Experiment (DOE) for process development and validation

o  Developing process control charts

o  Determining process capability indices.

The Quality System Regulation (QSR) for medical devices states that manufacturers should take steps, where appropriate, for establishing and maintaining procedures with which to identify valid statistical techniques needed to establish, control, and verify that the process capability and product characteristics are acceptable.

Methods are specified in 21 CFR and guidance documents

Both 21 CFR and guidance documents emphasize the need for statistical methods from discovery through product discontinuation. While 21 CFR specifies the suitable statistical procedures needed to establish both in-process and final specifications; the guidance documents require applying statistical methods for development and validation of measurement systems, process understanding using Quality by Design (QbD) principles, process validation, as well as ensuring that the manufacturing process is in a state of control and is capable.

Even though many statistical methods may be applied to fulfil this part of the QSR; there exist a few commonly accepted methods that all companies can and preferably should use for:

o  Developing acceptance criteria

o  Ensuring accurate and precise measurement systems

o  Fully characterizing manufacturing processes

o  Monitoring and controlling process results, and

o  Selecting an appropriate number of samples.

Learn the dynamics of statistical methods

The nitty gritty of application of statistical methods will be the teaching a two-day seminar from GlobalCompliancePanel, a leading provider of professional trainings for the regulatory compliance areas, will be offering. At this seminar, Heath Rushing, who is the cofounder of Adsurgo and author of the book Design and Analysis of Experiments by Douglas Montgomery: A Supplement for using JMP; will be the Director.

This course has been pre-approved by RAPS as eligible for up to 12 credits towards a participant’s RAC recertification upon full completion. To understand the areas of implementation of statistical methods that comply with the requirements set out in CFR 21 and guidance documents, please enroll for this session by visiting “Understanding the practical application of statistics”

A full description of statistical processes

This course provides instruction on the statistical methods for data analysis of applications related to the pharmaceutical, biopharmaceutical, and medical device industries. The Director will explain the appropriate statistical approaches: descriptive statistics, data intervals, hypothesis testing, ANOVA, regression, ANCOVA, and model building need to be applied. Upon establishment of competence in each of these areas; he will present the way these need to be applied in an industry-specific manner.

During the course of these two days, Heath will cover the following areas:

·        Describe and analyze the distribution of data

·        Develop summary statistics

·        Generate and analyze statistical intervals and hypothesis tests to make data-driven decisions

·        Describe the relationship between and among two or more factors or responses

·        Understand issues related to sampling and calculate appropriate sample sizes

·        Use statistical intervals to setting specifications/develop acceptance criteria

·        Use Measurement Systems Analysis (MSA) to estimate variance associated with: repeatability, intermediate precision, and reproducibility

·        Ensure your process is in (statistical) control and capable.

Article on “Statistical Sampling Plans for Medical Devices”

One of the important aspects of design control of medical devices is statistical sampling plans for medical devices. To gain an understanding of the idea of statistical sampling plans for medical devices, one needs to understand the process of medical device design controls.

Statistical sampling plans for medical devices needs to be seen in this background: Under Sec. 820.30 of Title 21 of Code of Federal Regulations (CRF) the FDA sets out requirements from medical device manufacturers -which want to market certain categories of medical devices in the US -for establishing and maintaining procedures to implements design controls into the device.

An understanding of design controls is necessary first

First of all, what are design controls? Design controls are linearly and logically described and recommended steps that manufacturers have to take for ensuring that they have developed what they meant to develop. In addition, design controls have to also be implemented to ensure that the final product is in line with the expectations and needs from the customer’s perspective.

Statistical sampling plans for medical devices come at a slightly later stage. Design controls pave way for the validation processes of design verification and design, which are done to ensure that the device design has met critical specifications or outputs and fulfill the requirements for the safety requirements, intended use, or specified application.

Verification and validation

This stage makes way for the next, which is fulfillment of design verification and validation (V&V), as required under Sec. 820.50 of 21 CFR. A core part of this code is the requirement from manufacturers for establishing and maintaining procedures to locate valid and proper statistical techniques for the process capability and product characteristics to be considered applicable. These are what constitute statistical sampling plans for medical devices

More of rule of thumb

Statistical sampling plans for medical devices need to be written and based on a well-established statistical foundation. However, the FDA does not prescribe a formal plan for writing down statistical sampling plans for medical devices. These are to be based more on rule of thumb. In other words, there are no acceptable limits violations under statistical sampling plans for medical devices. The statistical sampling plans for medical devices need to be implemented on a case-to-case basis, based on the device’s characteristics and features.

In arriving at statistical sampling plans for medical devices, the FDA sets out the following rule:

Table 1

Binomial Staged Sampling Plans

Binomial Confidence Levels

able 2

Binomial Staged Sampling Plans

Binomial Confidence Levels

ucl = Upper Confidence Level

These constitute the core guidance for statistical sampling plans for medical devices.

Learn more on this topic by visiting: Article on “Statistical Sampling Plans for Medical Devices”

Statistics for Medical Professionals

Medical statistics, also called biostatistics, is an important area for medical professionals. Statistics and the medical professionals may not seem very easily associable with each other at first glance, but a deeper look suggests the connection between statistics and the medical profession.

Statistics is a set of data and tables. These figures are meant to offer understanding and perspectives on a number of issues. When it comes to the medical profession; statistics for medical professionals becomes very important to those in the field of public health. Every time a government or an international agency of a world body such as the UN undertakes a program on public health; statistics are of immense importance for medical professionals.

Many uses of statistics for medical professionalsStatistics for medical professionals is useful in helping them analyze public health issues. Detailed figures of the incidence of malaria for instance, are a very useful piece of statistics for medical professionals. This kind of statistics helps them determine the causes of the disease and helps them decide on the plan of action.

Statistics for medical professionals is also useful at the local level. A medical professional working in a town or village could benefit immensely when she has statistics meant for medical professionals. It helps the professional understand what local causes are giving rise to health issues. Statistics for medical professionals thus helps them tackle issues at the local as well as the global levels

A specialized fieldIn developed countries, statistics for medical professionals has become a full-fledged profession. It is finessed at graduate and postgraduate programs at which they study the essentials of statistics for medical professionals. They then carry out programs that are suited for their profession.

Statistics for medical professionals is used in a wide variety of disciplines. Usually, courses on statistics for medical professionals cover the following areas:

• Data Analysis of statistics for medical professionals
• Dealing with Missing Data
• Higher Issues in Trials
• Linear Regression and Correlation
• Logistic Regression
• Correlated Data analysis
• Continuous Data comparison between groups
• Survival Data analysis
• Risk, Rates and Odds of statistics for medical professionals
• Randomized Trials
• Observational Studies of statistics for medical professionals
• Categorical Data comparison between groups
• Calculations of Sample Size
• Testing of Estimation and Hypothesis

More information go through this link: https://www.globalcompliancepanel.com/seminar?Linkedin_SEO